Artificial Intelligence: Foundations, Theory, and Algorithms - Böcker

Responsible Artificial Intelligence

How to Develop and Use AI in a Responsible Way

Responsible Artificial Intelligence

How to Develop and Use AI in a Responsible Way

Geometry of Uncertainty

The Geometry of Imprecise Probabilities

Geometry of Uncertainty

The Geometry of Imprecise Probabilities

Foundation Models for Natural Language Processing

Pre-trained Language Models Integrating Media

Foundation Models for Natural Language Processing

Pre-trained Language Models Integrating Media

Non-prioritized Belief Change

Bridging Constraint Satisfaction and Boolean Satisfiability

Feature Selection for High-Dimensional Data

Hybrid Metaheuristics

Powerful Tools for Optimization

Feature Selection for High-Dimensional Data

Bridging Constraint Satisfaction and Boolean Satisfiability

Subjective Logic

A Formalism for Reasoning Under Uncertainty

Decision Diagrams for Optimization

Coordination of Complex Sociotechnical Systems

Self-organisation of Knowledge in MoK

Towards a Code of Ethics for Artificial Intelligence

Electronic Institutions

Applications to uHelp, WeCurate and PeerLearn

Hybrid Metaheuristics

Powerful Tools for Optimization

Subjective Logic

A Formalism for Reasoning Under Uncertainty

Decision Diagrams for Optimization

Coordination of Complex Sociotechnical Systems

Self-organisation of Knowledge in MoK

Towards a Code of Ethics for Artificial Intelligence

Heterogeneous Graph Representation Learning and Applications

Heterogeneous Graph Representation Learning and Applications

Machine Learning Safety

Machine Learning Safety

AI Ethics

A Textbook

AI Ethics

A Textbook

Multi-Modal Robotic Intelligence

An Active Perception Approach